Comparative bioinformatic analysis of KRAS, STK11 and KEAP1 (co-)mutations in non-small cell lung cancer with a special focus on KRAS G12C.

OBJECTIVES: Mutations in STK11 (STK11MUT) and KEAP1 (KEAP1MUT) occur frequently in non-small cell lung cancer (NSCLC) and are often co-mutated with KRAS. Several studies linked the co-occurrence of KRASMUT + STK11MUT, as well as KRASMUT + KEAP1MUT to reduced response to immune checkpoint inhibitors (ICI) and even a negative impact on survival. Data focusing STK11 + KEAP1 co-mutations or the triple mutation (KRAS + STK11 + KEAP1) are scarce. The recent availability of KRAS-G12C inhibitors increases the clinical relevance of those co-mutations in KRAS-mutated NSCLC. MATERIALS AND METHODS: We present a comprehensive bioinformatic analysis encompassing six datasets retrieved from cBioPortal. RESULTS: Independent of the treatment, triple mutations and STK11MUT + KEAP1MUT were significantly associated with a reduced overall survival (OS). Across treatments, OS of patients with a KRAS G12C triple mutation was significantly reduced compared to patients with KRAS G12C-only. Under ICI-therapy, there was no significant difference in OS between patients harboring the KRAS G12C-only and patients with the KRAS G12C triple mutation, but a significant difference between patients harboring KRAS non-G12C and KRAS non-G12C triple mutations. Triple mutated primary tumors showed a significantly increased frequency of distant metastases to bone and adrenal glands compared to KRAS-only mutated tumors. Additionally, our drug response analysis in cancer cell lines harboring the triple mutations revealed the WNT pathway inhibitor XAV-939 as a potential future drug candidate for this mutational situation. CONCLUSION: The triple mutation status may serve as a negative prognostic and predictive factor across treatments compared to KRASMUT-only. KRAS G12C generally seems to be a negative predictive marker for ICI-therapy.

Candidate drugs associated with sensitivity of cancer cell lines with DLST amplification or high mRNA levels.

Overexpression of the dihydrolipoamide S-succinyltransferase (DLST) is associated with poor outcome in neuroblastoma patients and triple-negative breast cancer (TNBC) and specifically with the oxidative phosphorylation (OXPHOS) pathway. Inhibitors of OXPHOS were previously suggested as a potential therapeutic strategy for a subset of patients with high-risk neuroblastoma. Here, we tested if cell lines with DLST amplifications or high mRNA levels were associated with sensitivity to 250 drugs from the Genomics of Drug Sensitivity in Cancer (GDSC) dataset by comparing them to cell lines without these changes. DLST-altered cell lines were more sensitive to 7 approved drugs, among these obatoclax mesylate, a BCL2 inhibitor that reduces OXPHOS in human leukemia stem cells. Moreover, several protein kinase inhibitors were identified to be efficient in cell lines with DLST amplifications or high mRNA levels, suggesting a vulnerability of DLST-altered cell lines for drugs targeting the ERK/MAPK pathway. Furthermore, increased DLST expression in cell lines with driver mutations in KRAS supported this relationship. We therefore conclude that, in addition to OXPHOS, protein kinases could be potential targets of therapy in the presence of DLST amplifications or high mRNA levels. The new drug candidates proposed here could serve in experimental testing on drug efficacy in knock-in cell lines and DLST-activated tumors.

Interactive webtool for analyzing drug sensitivity and resistance associated with genetic signatures of cancer cell lines.

PURPOSE: A wide therapeutic repertoire has become available to oncologists including radio- and chemotherapy, small molecules and monoclonal antibodies. However, drug efficacy can be limited by genetic heterogeneity. Here, we designed a webtool that facilitates the data analysis of the in vitro drug sensitivity data on 265 approved compounds from the GDSC database in association with a plethora of genetic changes documented for 1001 cell lines in the CCLE data. METHODS: The webtool computes odds ratios of drug resistance for a queried set of genetic alterations. It provides results on the efficacy of single compounds or groups of compounds assigned to cellular signaling pathways. Webtool availability: https://tools.hornlab.org/GDSC/ . RESULTS: We first replicated established associations of genetic driver mutations in BRAF, RAS genes and EGFR with drug response. We then tested the 'BRCAness' hypothesis and did not find increased sensitivity to the assayed PARP inhibitors. Analyzing specific PIK3CA mutations related to cancer and mendelian overgrowth, we found support for the described sensitivity of H1047 mutants to GSK690693 targeting the AKT pathway. Testing a co-mutated gene pair, GATA3 activation abolished PTEN-related sensitivity to PI3K/mTOR inhibition. Finally, the pharmacogenomic modifier ABCB1 was associated with olaparib resistance. CONCLUSIONS: This tool could identify potential drug candidates in the presence of custom sets of genetic changes and moreover, improve the understanding of signaling pathways. The underlying computer code can be adapted to larger drug response datasets to help structure and accommodate the increasingly large biomedical knowledge base.